An Exploration Into Doctoral Students' Sense of Community and its Influence on the Formation of Informal Mentoring Relationships

This exploratory mixed method research project was designed to investigate an area of doctoral education that has received little attention in the past. This research focused specifically on the non-intellectual, hoped-for by-products of doctoral education; the dynamic processes of developing and maintaining both a sense of community and informal mentoring relationships. The design of the study captured the experiences of doctoral students and alumni at various time periods in the doctoral program. Participants represented a diverse group of students with differences in professional and academic backgrounds and life stages. A pilot study for this research suggested that the presence of a sense of community and informal mentoring may provide the necessary relationships to support this diversity. The primary question at the forefront of this study was: Do doctoral students feel connected to one another? Five subquestions were developed to address this research topic: Does a sense of community already exist and flourish in doctoral education? Are the programs and resources of the doctoral program organized to nurture the creation and maintenance of a sense of community? Is a sense of community a foundational element in the formation of naturally occurring relationships among doctoral students? What educational and socio-emotional benefits are associated with informal mentoring relationships during the doctoral experience? and Do doctoral students perceive a change in their development as stewards of their discipline over time? The principal methods used to investigate these research questions combined both quantitative and qualitative techniques in a concurrent time sequence. The quantitative portion of the study involved a questionnaire, while the qualitative portion involved two approaches; face-to-face interviews and an open-ended question at the end of the questionnaire. Findings from the study indicated that the presence of both sense of community and informal mentoring enhance the overall quality of doctoral education. Program elements that enhanced or hindered connection between students were identified. Both the dynamics and the emotional, social, and academic benefits of informal mentoring were elucidated. Over time participants perceived changes in their development of the qualities assqciated with stewardship. This study brought the "hoped-for by-products" associated with doctoral education from the background shadows to an illuminated position at the forefront of inquiry.

Community and the Recognition of the Other: A Levinasian Examination of The City, Inc. 1987-1992

This case study examines how The City, Inc.’s work within North and South Minneapolis, Minnesota neighborhoods from 1987 and 1992 was framed within a compilation of articles drawn from prominent Twin Cities’ daily newspapers. Positioned within a conceptual framework based on the ethical philosophy of Emmanuel Levinas, this study explores how the idea of community, as constructed and reinforced through organizational initiatives and local print media, impacts the everyday relationships of those within and between communities. Framed within a discourse analysis, Levinasian ethics considers what aspects of community discourse restrict and oppress the relation with the other. The study concludes by suggesting how the identified aspects of conditional belonging, finding the trace, and building community can be valuable in offering an alternative to assessment-style research by considering the relationship and responsibility of the one for the other.

The images produced by La Presse de Montréal of the Black community and crime

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

“Spatial and Temporal Variation of Phytoplankton Community and Their Growth Limiting Factors in Cochin Backwater”

The influence of salinity on phytoplankton varies widely, because different species have different salinity preferences. Like marine and aquatic species, many phytoplankton species exhibit tolerance to certain salinity, beyond which, it can inhibit their growth. Light is the most important factor that influences phytoplankton growth. In aquatic environments (lakes, sea or estuary) the light incident on the surface is rapidly reduced exponentially with depth (Krik, 1994). In estuaries, the major factor influencing the light availability is the suspended particulate matter, which attenuates and scatters the light. The light changes with time of the day and the season, affecting the amount of light penetrating the water column. Similarly, biological factor like copepod grazing is a major factor influencing the standing crop of phytoplankton. The copepod can actively graze up to 75% of the phytoplankton biomass in a tropical estuary (Tan et. al., 2004). It is in the context that the present study investigates the salinity, light (physical factors) and copepod grazing (biological factor) phytoplankton as the factors controlling phytoplankton growth and distribution

Predicting sense of community and participation by applying machine learning to open government data

Community capacity is used to monitor socio-economic development. It is composed of a number of dimensions, which can be measured to understand the possible issues in the implementation of a policy or the outcome of a project targeting a community. Measuring community capacity dimensions is usually expensive and time consuming, requiring locally organised surveys. Therefore, we investigate a technique to estimate them by applying the Random Forests algorithm on secondary open government data. This research focuses on the prediction of measures for two dimensions: sense of community and participation. The most important variables for this prediction were determined. The variables included in the datasets used to train the predictive models complied with two criteria: nationwide availability; sufficiently fine-grained geographic breakdown, i.e. neighbourhood level. The models explained 77% of the sense of community measures and 63% of participation. Due to the low geographic detail of the outcome measures available, further research is required to apply the predictive models to a neighbourhood level. The variables that were found to be more determinant for prediction were only partially in agreement with the factors that, according to the social science literature consulted, are the most influential for sense of community and participation. This finding should be further investigated from a social science perspective, in order to be understood in depth.